1. Field of the Invention
Embodiments of the present invention relate to computer application power consumption measurement, and in particular to estimating the power consumption of an application on a distributed mix of computer resources, servers and storage in a data center.
2. Background Information
The electrical power consumption costs of computer datacenters has been growing steadily and is a significant part of an enterprise's operating costs. Besides generally controlling and limiting all costs, the actual runtime costs of particular program applications being run need to be accounted for and charged to the corresponding customers, projects, and departments. One goal in systems management is being able to correlate the power consumption of data center servers, storage, and cooling to individual applications even though they run on a mix of resources.
Power consumption of an electrical appliance can be measured simply and directly by a discrete electrical instrument, such as a power meter. But the measurement of the power consumption of the individual constituent components of a computer system is far less practical and affordable.
At idle, computer systems and data storage units will typically draw a consistent, steady current. It isn't until the operating system and application programs are run on them that the power consumption goes up.
Modern computer systems can run multiple applications at the same time, and the work for those applications can be distributed across many discrete resources. Even if hardware could be employed to measure the power consumption of each of these component resources in real time, it would be difficult to determine how much power was being consumed by each particular application when more than one application is running.
Being able to gauge how much power is being consume, or will be consumed by each application is important to being able to track operational costs, resource capacity, and cooling demands. It can also be key to resource planning and job prioritization. Some of the best electrical power rates can be had if the peak power demands of the computer resources are limited to contracted maximums.